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The purpose of this paper is to examine recent developments pertaining to China’s shadow banking sector. Shadow banking has the potential not only to be a beneficial contributor to continued economic growth, but also to contribute to systematic instability if not properly monitored and regulated. An assessment is made in this paper as to whether shadow banking is beneficial or harmful to China’s economic growth.

The authors start with providing an overview of shadow banking from a global perspective, with information on its recent growth and importance in selected countries. The authors then focus directly on China’s shadow banking sector, with information on the various entities and activities that comprise the sector. Specifically, the authors examine the interconnections between shadow banking and regular banking in China and the growth in shadow banking to overall economic growth, the growth in the money supply and the growth in commercial bank assets.

Despite the wide range in the estimates, the trend in the size of shadow banking in China has been upward over the examined period. There are significant interconnections between the shadow banking sector and the commercial banking sector. Low deposit rate and high reserve requirement ratios have been the major factors driving its growth. Shadow banking has been a contributor, along with money growth, to economic growth.

The authors argue that shadow banking may prove useful by diversifying China’s financial sector and providing greater investments and savings opportunities to consumers and businesses throughout the country, if the risks of shadow banking are adequately monitored and controlled.

To the authors’ knowledge, this paper is among the few to systematically evaluate the influence of shadow banking on China’s economic growth.

To explain the shadow banking regime that will be enforced in the European Union by local regulators starting in January 2017.

Recognising the regulatory-induced difficulties in the process of identifying certain types of clients (investment funds) as shadow banking entities, this article provides a decision tree for the shadow banking classification process in order to aid the impacted institutions with the assessment of their clients. With this in mind, the article advises the impacted institutions on the specific steps that should be taken when assessing investment funds for shadow banking flags. Furthermore, the article provides insights into the information required to conduct the shadow banking classification process.

The regime requires the impacted institutions to assess their clients for shadow banking flags in order to impose limits on credit lines to clients classified as shadow banking entities. The US regulatory jurisdiction will be impacted over a longer term.

The recommendations in this article will be especially useful for investment funds to ensure that the relevant information is clearly stated in their prospectuses in order to avoid being classified as shadow banking entities.

This paper aims to document the impact of shadow banking on non-performing loans (NPLs) of publicly listed banks in an international setting.

This paper uses the data from 27 countries and various estimation strategies to test the arguments presented in this paper. The sample covers the period between 2002 and 2020.

The empirical results suggest that banks headquartered in countries with high shadow banking activity have fewer NPLs than otherwise similar banks headquartered in countries with low shadow banking activity. The findings remain qualitatively the same in different sub-samples and after replacing the main variables with their alternate proxies. The paper also shows that this relationship is sensitive to bank-specific characteristics. Moreover, the paper also indicates that the stringency of banking regulations weakens the relationship between shadow banking and NPLs.

The study’s data limitations prevent a detailed year-by-year analysis of NPLs and shadow banking, restricting insights into their evolving dynamics. In addition, the focus on country-level shadow banking data limits the exploration of how multinational banks’ activities in various jurisdictions impact individual banks’ NPLs.

The paper not only documents the effect of shadow banking on NPLs but also shows that the relationship between shadow banking and NPLs weakens as banking regulations become more stringent.

The purpose of this paper is to analyze the network path and internal mechanism of risks’ cross-contagion between shadow banks and design strategies for preventing risk infection between shadow banks.

Using the complex network theory, analyze the mechanism of risks’ cross-contagion between shadow banks from the credit network, business relationship network (BRN) and social network (SN); the cross-contagion mechanism using the structural equation model on the basis of China’s shadow banks is tested; based on the three risk infection paths, the prevention and control strategies for risk infection using the mathematical models of epidemic diseases are designed.

There are three network risk contagion paths between shadow banks. One, the credit network, risks are infected crossly mainly through debt and equity relationships; two, the BRN, risks are infected crossly mainly through business network and macro policy transmission; three, investor SN, risks are infected crossly mainly through individual SN and fractal relationships. The following three strategies for preventing risk’s cross-contagion between shadow banks: one, the in advance preventing strategy is more effective than the ex post control strategy; two, increasing the risk management coefficient; three, reducing the number of risk-infected submarkets.

The research of this study, especially the strategies for preventing the risks’ cross-contagion, could provide theoretical and practical guidance for regulatory authorities in formulating risk supervision measures.

This study investigates the interrelationships between competitions in different banking markets and shadow banking for the Chinese banking industry over the period 2003–2017. The current study also examines the determinants of competition in different banking markets and the factors influencing the size of shadow banking.

Bank competition is measured by the Boone indicator, while the relationship between bank competition and shadow banking is examined through a three-stage least square estimator.

The findings suggest that a larger volume of shadow banking leads to a decline in the level of competition in the deposit market, loan market and noninterest income market, while an increase in the level of competition in the loan market, deposit market and noninterest income market leads to an expansion of shadow banking. The authors find that higher bank risk and higher developed of stock market reduce the competitive condition in the loan market, and the competition in the deposit market will be enhanced by higher levels of banking sector development and higher levels of inflation, but bank diversification will reduce the level of competition in the deposit market. The authors further find that higher bank profitability and higher stock market development reduce bank competition in the noninterest income market. Finally, the results show that larger bank size and higher development of stock market reduce the size of shadow banking in China, but higher economic growth increases the size of shadow banking.

This is the first piece of research investigating the relationship between bank competition and shadow banking. This will also be the first piece of research examining the determinants of competition in different banking markets and also the factors influencing the size of shadowing banking in China.

The paper models the financial interconnectedness and systemic risk of shadow banks using Granger-causal network-based measures and takes the Indian shadow bank crisis of 2018–2019 as a systemic event.

The paper employs pairwise linear Granger-causality tests adjusted for heteroskedasticity and return autocorrelation on a rolling window of weekly returns data of 52 financial institutions from 2016 to 2019 to construct network-based measures and calculate network centrality. The Granger-causal network-based measure ranking of financial institutions in the pre-crisis period (explanatory variable) is rank-regressed with the ranking of financial institutions based on maximum percentage loss suffered by them during the crises period (dependent variable).

The empirical result demonstrated that the shadow bank complex network during the crisis is denser, more interconnected and more correlated than the tranquil period. The closeness, eigenvector, and PageRank centrality established the systemic risk transmitter and receiver roles of institutions. The financial institutions that are more central and hold prestigious positions due to their incoming links suffered maximum loss. The shadow bank network also showed small-world phenomena similar to social networks. Granger-causal network-based measures have out-of-sample predictive properties and can predict the systemic risk of financial institutions.

The study considers only the publicly listed financial institutions. Also, the proposed measures are susceptible to the size of the rolling window, frequency of return and significance level of Granger-causality tests.

Supervisors and financial regulators can use the proposed measures to monitor the development of systemic risk and swiftly identify and isolate contagious financial institutions in the event of a crisis. Also, it is helpful to policymakers and researchers of an emerging economy where bilateral exposures' data between financial institutions are often not present in the public domain, plus there is a gap or delay in financial reporting.

The paper is one of the first to study systemic risk of shadow banks using a financial network comprising of commercial banks and mutual funds. It is also the first one to study systemic risk of Indian shadow banks.

This paper aims to survey available data sources and put China’s shadow banking system in perspective. Although bank loans still account for the majority of credit provided to China’s real economy, other channels of credit extension are growing rapidly. The fast expansion of shadow banking has spurred wide concerns regarding credit quality and financial stability.

This paper explores various data sources, provides an overview of shadow banking activities in China, discusses their close ties with banks and summarizes regulatory issues. Extensive descriptive data are included to provide a comprehensive picture of the nature of shadow banking activities in China. In particular, institutions and products are discussed in great details.

While China’s shadow banking system is by no means simple, it does not (yet) involve the extensive use of financial derivatives. Rather, shadow banking credit is often directly extended to the real economy. In addition, shadow banks are typically interconnected with commercial banks in various ways. The expanding scale and constantly evolving structure of the shadow banking system has posed challenges for financial regulators.

This paper attempts to quantify the scale and scope of China’s shadow banking activities and provides a consistent framework as the basis for cross-country comparison of shadow banking systems. This is one of the first scholarly research products that discusses the origin, nature and risks of China’s shadow banking system in a regulatory context.

Shadow banks or non-bank financial intermediaries (NBFIs) are facilitators of credit, especially in emerging market economies (EMEs). However, there are certain risks associated with them, such as their unchecked leverage and interconnectedness with the rest of the financial system. In light of this, the present study analyses the impact of the growth of shadow banks on the stability of the banking sector and the overall stability of the financial system. The authors further examine the effect of the growth of finance companies (a type of NBFIs) on financial stability.

The study employs data of 11 EMEs (monitored by the Financial Stability Board (FSB)) for the period 2002–2020 to examine the above relationships. Panel-corrected standard errors method and Driscoll–Kray standard error estimation are deployed to conduct the analysis.

The results signify that the growth of the shadow banking sector and the growth of lending to the shadow banking sector are negatively associated with the stability of the banking sector and increases the vulnerability of the financial system (overall instability). This implies that the higher the growth of the shadow banks, the higher the financial fragility. Finance companies are also found to negatively affect financial stability. These findings are validated by different estimation methods and point out the risks posed by the NBFI sector.

The extant study builds a composite index (Financial Vulnerability Index (FVI)) to measure financial stability; thus, the findings contribute to the evolving literature on shadow banks.

Wealth Management Products (WMPs) are the largest and most crucial component of China's Shadow banking, which are off the balance sheet and considered as a substitute for deposits. Commercial banks in China are involved in the issuance of WMPs mainly to; evade the regulatory restrictions, move non-performing loans away from the balance sheet, chase the profits and take advantage of yield spread (the difference between WMPs yield and deposit rate).

In this study, the authors investigate what bank related characteristics and needs; influenced and prompted the issuance of WMPs. By using a quarterly panel data from 2010 to 2019, this study performed the fixed effects approach favored by the Hausman specification test, and a feasible generalized least square (FGLS) estimation method is employed to deal with any issues of heteroscedasticity and auto-correlation.

This study found that there is a positive and significant association between the non-performing loan ratio and the issuance of WMPs. Moreover, profitability and spread were found to play an essential role in the issuance of WMPs. The findings of this study suggest that WMPs are issued for multi-purpose, and off the balance sheet status of these products makes them very lucrative for regulated Chinese commercial banks.

Non-guaranteed WMPs are considered as an item of shadow banking in China, as banks do not consolidate this type of WMPs into their balance sheet; due to that reason, there is no individual bank data available for the amount of WMPs. The authors use the number of WMPs issued by banks as a proxy for the bank's exposure to the WMPs business.

From a regulatory perspective, this study helps regulators to understand the risk associated with the issuance of WMPs; by providing empirical evidence that Chinese banks issue WMPs to hide the actual risk of non-performing loans, and this practice could mislead the regulators to evaluate the bank credit risk and loan quality. This study also identifies that Chinese banks issue WMPs for multi-purpose; this can help potential investors to understand the dynamics of WMPs issuance.

This research is innovative in its orientation because it is designed to investigate the less explored wealth management products (WMPs) issued by Chinese banks. This study's content includes not only innovation but also contributes to the existing literature on the shadow banking sector in terms of regulatory arbitrage. Moreover, the inclusion of FGLS estimation models, ten years of quarterly data, and the top 30 Chinese banks (covers 70% of the total Chinese commercial banking system's assets) make this research more comprehensive and significant.

This paper aims to examine the evolution of house prices in China and especially the effects of different financing channels on China’s house prices.

The author use the own theoretical framework and proceed to test the testable hypotheses by using the autoregressive distributed lag bounds test approach for cointegration analysis and the unrestricted error correction model. Quarterly time series data from Q1 2002 to Q2 2016 are used.

The results suggest that in the short run, bank loans to real estate development and scale of shadow banking have significant positive effects on house prices. In the long run, the scale of shadow banking and disposable income affects house prices positively and significantly.

This study provides more insights into how and to the extent different financing channels affect China’s house prices, particularly the impact of shadow banking on the house prices.